The Web 3.0 Conference in New York last week was a visible success. Attendance was good, and so it seems that the organizers are making money. That is significant in a recession, when many conferences that were announced have had to be suddenly canceled due to lack of interest. At a more qualitative level, the Web 3.0 Conference had a good mix of different types of people. It was not an echo chamber. Personally, I found the conversations more stimulating than average for a conference.]]>
Who Was There?
This a personal impression based on actual conversations, not based on the attendance list.
- Serial entrepreneurs seeking their next big venture. I spoke to two of them. What was interesting was that both were very successful, knew very little about the semantic Web (they were there to learn), and were extremely open to seeking where the opportunities lie. In other words, they were at the formative stages of their ventures.
- Semantic Web pioneers. Conference organizers made it very clear they did not want an echo chamber of SemWeb experts talking to SemWeb experts. They wanted SemWeb experts to connect with business people who had problems that needed solving. That seemed to be happening.
- Connectors, money guys, promoters. There were quite a few of these, usually a sign that something is either happening or about to happen.
- Publishers. Well, the conference was in New York, so you would expect publishers, of all types, both big and small.
- Semantic Web ventures that are already getting traction. Most of these appearances took the form of speakers and conference sponsors.
Where Is the Value in this Next Phase of the Web?
This is what the serial entrepreneurs were asking. Here is my view after a few days of reflection. Three big market opportunities will see semantic Web technology used in different ways in the near term:
- Scientific/technical/medical (STM) publishing,
- Market research information created from random social media chatter,
- Improved advertising relevance.
Each of these deserves closer inspection.
Scientific/Technical/Medical Publishing
Open-source data will disrupt traditional data publishing -- in particular and immediately STM publishing -- similar to how open-source software disrupted the software industry. STM publishing is a market worth more than $10 billion, so this is significant. Similar forces will play out in financial, legal, and other data-rich industries, but STM is likely to be in the vanguard for the following reasons:
- Everybody in the eco-system wants this to happen except the current publishers. Governments and institutions that fund research want it to be freely available. The authors are not like book authors; they don't get paid per book sold. They want wide distribution and peer recognition.
- There are huge benefits to the raw data being machine-readable, not the least of which is that the data can be used for further analysis, rather than be squeezed into the artificial format designed for print journal distribution.
- Scientists and researchers will use the semantic Web tools that consumers and business people consider too complex (until some great UI designers take on this challenge).
As in any market transition, there will be winners and losers.
Winners:
- Scientists and researchers,
- (Indirectly) everyone who benefits from the products created by scientists and researchers,
- New publishers (or some other entity) that add enough value to free source data that they are still able to charge for it.
Losers:
- Traditional STM publishers who cling too tightly to their current cash cow and so cannot effectively ride the next wave.
After it goes through the STM sector, this wave will crash through other data-rich publishing markets, such as:
- Finance
- Law
Market Research Information Created from Social Media Chatter
The Web 2.0 era has unleashed an enormous amount of social media chatter. These conversations are inconsequential to all except the participants... until, that is, they are aggregated, structured, and analyzed. This is not simple to do, as security and intelligence agencies have long understood. When you can record any conversation you like, you quickly find that discovering something useful is really hard. Historically, only intelligence agencies have had access to this volume of chatter. And the public has only had access to conversations between "important" people about important subjects. Multiply the chat you and I had about what we had for breakfast a few million times, and someone might get interested, specifically someone in the market research industry.
Market research is a large industry. Obtaining explicit data about people by getting them to fill in surveys is becoming increasingly hard and expensive. Perhaps gathering data about what people are actually talking about and deriving something useful from that would be easier.
This is not likely that elusive native revenue model for social media. But it could be a useful add-on revenue stream. Semantic Web ventures that can pay social media sites for raw data, extract that data, add meaning, and sell it to marketers could do very well. That won't be easy to do well, though.
Improved Advertising Relevance
AdWords represented a massive advance in advertising relevance. It changed the advertising and media industries beyond recognition and made Google the most powerful technology company on the planet.
But is this as far as we can go with advertising relevance? Almost certainly not. Whether Google or another venture leverages the semantic Web, there is little doubt that semantic Web technology will improve advertising relevance. Quite how to do this is the subject of another post.
Disclosure: Web 3.0 was a sponsor of ReadWriteWeb, but we have no other financial interest in the event.
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